PCB Edge Defect Detection Using Multi-Sensor Differential Measurement
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Solution Overview
Problem
Conventional automated systems for detecting defects on the edges of objects like printed circuit boards often fail to accurately identify defects due to board shifts or width fluctuations, leading to false positive readings and improper identification of non-defective boards as defective.
Innovation Solution
An automated system utilizing a configuration of at least four electronic sensors, including laser or ultrasonic sensors, positioned on both sides of an object inspection line, calculates a sum of sensor measurements to compare against a threshold value, accounting for potential shifts and width fluctuations, thereby enhancing defect detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single electronic sensor is used to detect board edges, then the device complexity is low, but the measurement precision deteriorates due to board shifts and width fluctuations causing false positive readings
Solution Approach 1:
The inspection system divides the detection task into multiple independent sensor measurements. Instead of using a single sensor, the patent employs at least four sensors positioned at different locations (first and second sensors on one side, third and fourth sensors on the opposite side) to independently measure board edges. This segmentation allows each sensor to capture localized edge information, reducing the impact of board shifts and width fluctuations on overall measurement accuracy.
Solution Approach 2:
The patent transitions from one-dimensional single-point measurement to multi-dimensional distributed measurement. By positioning sensors at multiple locations across the board width and using differential calculations between opposing sensors, the system creates a multi-dimensional measurement space that can compensate for positional variations and width fluctuations, thereby improving measurement precision without excessive complexity.
2Measurement precision
If multiple sensors are used to improve defect detection accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent combines multiple sensor measurements into a unified differential calculation framework. By merging the readings from opposing sensors (first with fourth, second with third) and performing differential operations, the system consolidates multiple measurement streams into meaningful defect detection signals. This merging approach allows the system to leverage multiple sensors for improved precision while managing complexity through systematic data integration.
Solution Approach 2:
The patent employs a symmetric sensor arrangement where sensors are positioned in corresponding locations on opposite sides of the board. This copying of the sensor configuration across the board width creates redundant measurement paths that can be differentially processed. The symmetric copying ensures that width fluctuations and shifts affect opposing sensors equally, allowing their effects to cancel out in differential calculations.
3Reliability
If a higher detection threshold is used to account for board width fluctuations, then the reliability of defect identification improves, but the measurement precision deteriorates because the threshold increases from ε to ε+λ
Solution Approach 1:
The patent extracts and eliminates the unwanted width fluctuation component from the measurement signal through differential calculation. By subtracting measurements from opposing sensors, the system separates the useful defect information from the nuisance width variation. This extraction process removes the λ (width fluctuation) component from the final defect determination, allowing the system to maintain high reliability without sacrificing measurement precision or requiring increased thresholds.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively reduces false positive readings by accounting for board misalignments and width variations, ensuring accurate identification of defective edges and preventing the misclassification of non-defective boards.
Implementation Method 1
electronic sensors that are able to detect object edges (such as electronic sensors that are used as position sensors or edge measurement sensors)
Implementation Method 2
electronic sensors that are able to detect object edges (such as electronic sensors that are used as position sensors or edge measurement sensors)
Data Source
AI summary
An automated system and method for detecting substantial edge defects on an object that can degrade or impede proper object performance. The defects, such as chips, cracks, or bumps, if sufficiently substantial, can interfere with the proper operation of the object. The inspection may be performed with four electronic sensors, two on each side of the object, or with two electronic sensors that each take two sets of measurements spaced apart by a certain time interval. Sensor measurements are periodically obtained and used by a controller to calculate a value based on the four sensor measurements. The calculated value is compared to a threshold to determine whether or not any defects are significant.